Data analysis of cells undergoing excitation contraction coupling as detected on real-time cell analysis (rtca) instruments

ABSTRACT

A method of determining a beating parameter of cells that undergo excitation contraction coupling, the method including providing a cell analysis device having a substrate and a sensor that measures cell adhesion or attachment to the substrate in millisecond time resolution; adding excitable cells capable of undergoing excitation contraction coupling to the substrate; monitoring cell adhesion or attachment of the excitable cells to the substrate in millisecond time resolution; and calculating one or more beating parameters from the monitored adhesion.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a continuation of U.S. Ser. No. 13/109,809, filed May 17, 2011,which is a continuation in part of U.S. patent application Ser. No.12/435,569, filed on May 5, 2009, which claims benefit of priority toU.S. provisional patent application Ser. No. 61/191,684, filed on Sep.11, 2008 and U.S. provisional patent application Ser. No. 61/126,533,filed on May 5, 2008, the contents of each are herein incorporated byreference in their entirety.

U.S. Ser. No. 13/109,809 also claims benefit of priority to U.S.provisional patent application Ser. No. 61/345,867 filed on May 18,2010; the contents of which are herein incorporated by reference intheir entirety.

TECHNICAL FIELD

The invention relates to cell based assays that monitor excitationcontraction coupling of cells and more specifically to methods fordetermining cell beating parameters by monitoring cell adhesion orattachment of cells that undergo excitation contraction coupling.

BACKGROUND OF THE INVENTION

Cardiac safety pharmacology is the study of the potential undesirablepharmacodynamic effects of a substance on heart function in relation toexposure to the substance in the therapeutic range and above. Cardiacsafety is a major concern in current drug development. Since 1981, atleast 10 blockbuster drugs have been withdrawn from the market due tocardiac liability, defined as potentially undesirable effects on heartfunction. Furthermore, cardiac safety is a major reason for late stageattrition of drug candidates during development.

There are three non-mutually exclusive ways that non-cardiac drugs maylead to cardiac liability. Directly, cardiotoxic drugs are drugs whichcause damage via necrosis or apoptosis, such as anthracyclines.Pro-arrhythmic drugs are drugs which induce arrhythmia. Indirectly,cardiotoxic drugs are drugs which indirectly affect cardiac function,such as by causing narrowing of the arteries.

Directly, cardiotoxic drugs directly affect the viability ofcardiomyocytes and therefore heart function. A prominent class of drugsin this category is chemotherapeutic drugs, such as anthracyclines.Mortality due to cardiac disease is thought to be 8-fold higher forsurvivors of childhood cancers who have received chemotherapy. Thesedrugs are thought to disrupt iron metabolism, generating harmful oxygenradical species which ultimately cause mitochondrial damage andapoptosis.

Pro-arrhythmic drugs induce arrhythmia. Normal synchronized contractileactivity of cardiomyocytes is the result of orchestrated ion currentspassing across the cell membrane via ion-specific channels and couplingwith the specialized cytoskeleton. Disturbances in the ionic movement ofinterference with ion channel activities may lead to arrhythmia. It isbelieved that one of the primary targets of pro-arrhythmic drugs is theERG channel, which is responsible for delayed repolarization ofcardiomyocytes. ERG channel blockage may lead to QT elongation and thismay cause a fatal form of ventricular arrhythmia called Torsades dePointes (TdP). Between 1990 and 2006, 10 blockbuster drugs have beenwithdrawn from the market due to induction of TdP. The drugs that havebeen associated with cardiac arrhythmia and removed from the market areprenylamine, terodiline, sparfloxacin, sertindole, terfenadine,astemizole, grepafloxacin, cisapride, droperidol, and levacetylmethadol.

Excitation-contraction coupling (ECC) is a term used to describe thephysiological process of converting an electrical stimulus to amechanical response. The process is fundamental to muscle physiology,wherein the electrical stimulus may be an action potential and themechanical response is in the form of contraction. Although ECC has beenknown generally over half a century, it is still an active area ofbiomedical research.

Cardiomyocytes are specialized muscle cells of the myocardium that arecapable of excitation-contraction coupling. Cardiomyocytes are commonlyused in biomedical research to assess the cardiotoxicity of potentialdrugs or treatments. Two conventional approaches to assesscardiotoxicity are primarily used. A first approach involves isolationof cardiomyocytes directly from a mammalian species such as rats anddogs followed by electrophysiological studies on the isolatedcardiomyocytes. However, this approach suffers from being extremelylabor-intensive, time consuming and costly and at the same time not veryamenable to the high throughput demands of pharmaceutical industry. Analternative approach utilizes cell-based assay models, whichheterologously express specific ion channels such as hERG channels orvoltage-gated calcium channels. These cardiac ion channels have beenenvisioned as possible molecular targets through which drugs couldinduce cytotoxicity. These cell-based systems allow assessment ofdrug-channel interaction by monitoring the effect of the drug oncurrents produced by different channels in cultured cells using atechnique known as “patch clamping.” Patch clamping isolates regions ofthe cell membrane containing channel proteins and measures changes inelectrical potential difference. However, use of this method in highthroughput requires automation of patch clamping in an array format withreliable giga seal, which even though is becoming increasing available,is not yet widespread. In addition, cardiac toxicity may occur by othermechanisms that could be possibly missed by this type of targetedapproach. An alternative to in vitro ion-channel recording assays aswell as the labor-intensive isolation of primary tissue is thedifferentiation of embryonic stem (ES) cells into cardiomyocytes. Theutility of ES cells as a treatment for various chronic diseases hasreceived much attention in recent years. Mammalian ES cells are selfrenewing cells derived from the inner cell mass of a blastocyst stageembryo which can be differentiated into multiple different cell types.It has been demonstrated that the mouse ES cells as well as human EScells can be differentiated into cardiomyocytes which retain the abilityto beat in culture. Differentiation of ES cells first involves anintermediate in vitro developmental stage in which ES cells form compactcell structures known as embryoid bodies. These embryoid bodies caninduce the developmental program of ES cell differentiation intomultiple cell types including cardiomyocytes, which are distinguished inculture by their ability to undergo spontaneous beating. These ESderived in vitro differentiated cardiomyocytes recapitulates the normaldevelopment of cardiomyocytes as evidenced by the stage-specificexpression of cardiomyocyte specific genes. All the known transcriptionfactors, ion channels and structural proteins that are part of normalheart development and function in vivo are also expressed in ES-derivedcardiomyocytes.

Even though high throughput to medium throughput systems have beendeveloped for functional characterization of cell lines heterologouslyexpressing the gene for specific ion channels, high throughputtechniques for functional characterization of more complex systems suchas cardiomyocytes have been limited. Technologies designed to assesscardiomyocyte behaviour and function and the effect of drugs and othermanipulations in vitro can be divided into two different approaches. Oneapproach involves long term assessment of cardiomyocyte viability forexample in response to certain compounds. Such assays are typically endpoint assays designed to measure a cellular component such as ATP whichcorrelates with the degree of viability of the cells. The other approachinvolves studying short term effect of drugs and compounds on beatingfunction of cardiomyocytes. High throughput techniques for short termfunctional characterization of ion channels and other targets incardiomyocytes has been rather challenging and limited. The availablesystems typically only monitor a single cardiomyocyte or a small numberof cardiomyocytes at a time with very limited throughput.

SUMMARY OF THE INVENTION

The invention addresses the need for further study of cardiomyocytes andtheir response to therapeutic agents by establishing a number beatingparameters which may be used to assess the heath, function and responseof the cardiomyocytes to potential treatment of drugs or chemicalcompounds. The above is accomplished by providing a method ofdetermining one or more beating parameters for use in cardiomyocytebeating analysis. The method includes providing a cell analysis deviceincluding wells, each well including a sensor capable of monitoringbeating of cardiomyoctes in millisecond time resolution; addingcardiomyocytes to the wells; monitoring the beating of thecardiomyocytes in millisecond time resolution to obtain a plurality ofbeating measurements; and calculating one or more beating parametersfrom the plurality of beating measurements.

The cell analysis device should be able to measure cardiomyocytesbeating in millisecond time resolution. In some embodiments, the cellanalysis device is an impedance monitoring device, such as an impedancemonitoring device having a sensor formed from two electrode structures,each having substantially the same surface area. In other embodiments,the sensor is an optical sensor. Examples of suitable optical sensorsare those that can be used to detect or measure changes in cellmorphology, cell adhesion and cell number. Among these include aresonant waveguide or a resonant waveguide grating sensor.

In some embodiments, beating measurements are plotted over time to form,at least in part a beating curve. Beating parameters can then be derivedfrom the curve or corresponding data. Among the beating parameters ofparticular interest, include beating rate, beating amplitude, risingtime, falling time, beating period, IBD50, IBD10, IBD90, rising slope,falling slope, normalized beating rate, normalized beating amplitude,beating pattern similarity and beating rhythm irregularity.

Test compounds may be added to identify changes in beating parametersand thus the effect on cardiomyocytes. Accordingly, in some embodimentsa test compound is added to the wells at a number of differentconcentrations and a dose response curve (DRC) is constructed. Infurther embodiments, the methods include determining an IC50 or EC50value from the dose response curve. In other embodiments a test compoundis added to the wells to assess a potential difference in beatingparameters, which may be indicative of cardiotoxicity.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-B depict schematic drawings of one design of a cell-substrateimpedance measurement device of the present invention. FIG. 1A shows anonconductive substrate 101 with 16 electrode arrays or sensorsfabricated on the substrate. Each electrode array 102 includes twoelectrode structures. Each electrode structure comprises multipleelectrode elements. Each electrode array connects to two electricaltraces 103, with each of the two traces connected one of the twoelectrode structures. These electrical connection traces 103 from theelectrode array 102 are connected to the connection pads 104 at theedges of the substrate 101. As shown in FIG. 1A, each of the fourelectrode arrays in each of four quarters on the substrate 101 have oneof their electrical connection traces 103 connected to a commonconnection pad 104. Thus, for the depicted device there are four commonconnection pads 104, one for each quarter of the device. In addition,each electrode array has a separate electrical connection trace 103,connecting to an independent connection pad 104. Thus, there are total20 connection pads 104 at the edges of the substrate (101). In FIG. 1B asingle exemplary electrode array or sensor is shown. The electrode arrayhas two electrode structures, where each electrode structure comprisesmultiple electrode elements 105 shown here having a circle-on-linegeometry. In this electrode array structure, electrode elements 105 ofone electrode structure of the array alternate with electrode elements105 of the other electrode structure of the array. Each of the electrodestructures is independently connected to its electrode bus 106, in thiscase, by means of direct connection of the electrode elements 105 to theelectrode bus 106. Each electrode bus 106 forms an arc around theperimeter of the array, where the two buses of the array do not abut oroverlap. The electrically conductive connection traces 103 in FIG. 1Aconnect each bus with a connection pad 104 in FIG. 1A on the edge of thesubstrate 101 in FIG. 1A.

FIG. 2 depicts graphs demonstrating combined long term and short termmeasurement of cardiomyocytes beating over at least 7 days includingmeasurement in millisecond time resolution with corresponding cell indexvalues calculated from impedance measurements over beating periods atdays 3, 5 and 7.

FIG. 3 depicts graphs showing change in cell index in millisecond timeresolution before and after adding 190 nM of compound E4031, which ishas pro-arrhythmic effects.

FIG. 4 depicts a series of graphs showing the effect on cell index of acardiomyocyte cell population in millisecond time resolution before andafter adding petamidine, which prevents ERG transport to the membraneand thus a delayed adverse effect over 6 hours.

FIG. 5 depicts a series of graphs showing change in cell index inmillisecond time resolution of iPS cell-derived cardiomyocytes andmonitoring of the cardiomyocytes over 45 days.

FIG. 6 depicts millisecond time resolution charting of cell index ofcardiomyocytes tested with increasing concentration of pro-arrhythmicdrugs withdrawn from the US market, namely Droperidol, Astemizole,Cisapride, Sertindole and Terodiline.

FIG. 7 depicts a graphical representation of multiple cardiomyocytebeating periods and graphical illustration of features used in beatingparameters including positive peaks P1, P2, P3 . . . Pm; negative peaks−P1, −P2, −P3, . . . −Pm; and beating amplitude Amp-1, Amp-2, Amp-3 . .. Amp-m.

FIG. 8 depicts a graphical representation of a portion of a beatingperiod to demonstrate a rise and fall of beating amplitude includingtime points for 20% amplitude, 50% amplitude and 80% amplitude.

FIGS. 9A-D depicts graphs and an accompanying table resulting fromdynamic monitoring and characterization of mouse embryonic stem cellderived cardiomyocytes (mESCC) beating using impedance-based detection.FIG. 9A shows long term impedance monitoring of cells with arrowsdepicting time points for short term millisecond recording. FIG. 9Bshows beating activity and profile of mESCC at time points identified inFIG. 9A after cell seeding. The beating rate (1/min), amplitude (deltaCI), beat duration (IBD50; ms), Time to Max (ms) and Decay Time (ms)were quantified using the RTCA Cardio software and as described in theExamples section. The data represents the average of 8 wells −/+StandardDeviation. A total duration of 5 sec recording time is displayed. FIG.9C demonstrates blebbistatin, an inhibitor of myosin heavy chain ATPaseactivity, inhibits beating activity of mESCC, which is restored bywashing out the compound and replacing by normal growth media. FIG. 9Ddemonstrates that Blebibistain treatment of mESCC has no effect on fieldpotential recording as measured on Multi-Electrode Arrays.

FIGS. 10A-C depict graphs showing pharmacological assessment of ionchannel modulators measured using the impedance-based system on mouseembryonic stem cell derived cardiomyocytes (mESCC). Cells were seeded inthe wells of the E-PLATE (ACEA Biosciences Inc., San Diego, Calif.),monitored for 3 days using the RTCA Cardio system and treated with theindicated concentrations of each compound. The beating activity wasrecorded by the RTCA Cardio system as described in the Examples section.For each compound at the indicated time points 5 sec of beating activityis displayed with the exception of ERG which is total of 14 seconds ofbeating activity. The beating rate for each interval of beating activityis displayed as beats/min−/+SD; the data shown is one representativerecording from a total of at least 3 separate experiments. FIG. 10Ashows results from treatment with Isrdapine, an L-Type voltage-gatedcalcium channel inhibitor, FIG. 10B shows results from treatment with(S)-(−)Bay K 8644, an agonist of L-Type voltage-gated calcium channels,FIG. 10C shows results from treatment with chromanol, inhibitor of theslow delayed rectifier K⁺ current.

FIGS. 11A-C depict graphs showing pharmacological assessment of ERGchannels, sodium channels and ionotropic agents. FIG. 11A shows resultsfrom treatment with E4031, an inhibitor of ERG type K⁺ channel, FIG. 11Bshows results from treatment with Tetrodotoxin (TTX), inhibitor ofvoltage-gated Na⁺ channel, and FIG. 11C shows results from treatmentwith isoproterenol, an ionotropic agent and agonist of the β-adrenergicreceptor.

FIG. 12 depicts a table summarizing beating parameters includingnormalized beating rate, normalized amplitude and beating rateirregularity of the compounds tested in FIGS. 10A-C and FIGS. 11A-C.

FIGS. 13A and B depict graphs showing mechanism-based cardiotoxicityprofiling of cardiomyocytes using impedance-based devices. FIG. 13Ashows screening, in a dose-response manner in mESCC, 4 drugs which havebeen withdrawn from the market due to increased incidence of TdParrhythmia. For each compound a total of 5 sec of beating activity isdisplayed. For Astemizole, cisapride, droperide and sertindole thedose-response profiles are shown at 30 min, 15 min, 180 min and 165 minafter compound addition, respectively. The bottom row shows thedose-response for each of the compounds at the indicated time pointsbased on calculation of beat duration parameter as described in theExamples section. In FIG. 13B plateau oscillation profiles are inducedby all four compounds tested in FIG. 13A as well as E-4031, indicating acommon underlying mechanism; at total of 9 sec of beating profilerecording is displayed for each of the compounds.

FIGS. 14A-C depict graphs and results from treatment with doxorubicinand pentamidine. FIG. 14A shows mESCC treated with increasingconcentrations of doxorubicin. Dose-dependent impedance-based cellularprofiles were monitored for up to 24 hours after compound treatment. InFIG. 14B a total of 5 sec of recording is shown for each dose at thegiven time point. The beating activity is quantified in terms of beatingrate and displayed in each box. In FIG. 14C mESCC were seeded in thewells of E-PLATE (ACEA Biosciences, San Diego, Calif.) and on day 3treated with 20 μM Pentamidine. The beating activity was monitored atthe indicated time windows after compound treatment and quantified basedon beat duration as mentioned in the Examples section.

FIG. 15 depicts a table summarizing the screening results of 50compounds with potential cardiotoxic liability screened at 3 final doses(10 μM, 1 μM and 0.1 μM) using the RTCA Cardio system together withmESCC. For each compound both the lowest observed concentration (LOC)which resulted in an effect on mESCC and the resulting beating profilewas included.

DETAILED DESCRIPTION

The present invention addresses the need to provide methods to furtherimprove monitoring of excitation-contraction coupling in cardiomyocytesand excitable cells, such as for cardiac safety assessment and for thestudy of cardimyocyte function and differentiation. Specifically,embodiments of the invention describe label-free methods for monitoringcardiomyocytes in vitro and methods for effective comparison byestablishing a plurality of beating parameters. The methods are capableof continuously monitoring excitation-contraction coupling anddetermining the beating parameters in a relatively high-throughputmanner, which offers a unique approach to assessing the safety ofpotentially cardiotoxic treatments, which may not be readily apparent.The systems and methods can be used to assess both short term and longterm effects of substances on cardiomyocyte beating, viability andmorphology.

Monitoring Beating of Cardiomyocytes

While the invention relates primarily to methods for determining beatingparameters for beating analysis and comparison, it is important toobtain reliable beating measurements in millisecond time resolution.Millisecond time resolution preferably refers to the measurement oracquisition of data from at least two consecutive time points within 100milliseconds of one another. More preferably, the at least twoconsecutive beating measurements are performed in less than 40milliseconds. Still more preferably, the at least two consecutivemeasurements are performed in less than 20 milliseconds. In stillfurther embodiments the at least two consecutive beating measurementsare performed in less 10 milliseconds.

In one approach a device for monitoring the beating of cells may be anoptical-based system, which uses an optical sensor. Optical sensorstypically measure an optical property of the cell, which may relate cellmorphology, cell adhesion degree and/or cell number. Among the opticalsensors that may be used include resonant waveguide sensors or resonantwave guide grating sensors. For example, the resonant wave guide gratingsensor utilizes the resonant coupling of light into a waveguide througha diffraction grating. A polarized light, covering a range of incidentwavelengths, is directly used to illuminate the waveguide; light atspecific wavelengths is coupled into and propagates along the waveguide.The resonance wavelength at which a maximum in coupling efficiency isachieved is a function of the local refractive index at or near thesensor surface. When the cardiomyocytes are cultured and attached to thesurfaces of the resonant wave guide sensor, the local refractive indexon the sensor/cell interface would be affected by changes in cellmorphology, cell adhesion and other cellular properties. For example, arelocation or re-arrangement of certain cellular contents such as thechange in cell adhesion degree, or membrane refilling, recruitment ofintracellular proteins to activated receptors at the cell surface, orreceptor endocytosis, the change in cell morphology may all result inthe change in local refractive index, leading to a detectable change orshift in the maximum in coupling efficiency wavelength. The effect ofthe presence of the cells on a resonant wave guide grating sensor hasbeen explored based on the dynamic mass redistribution model. Thedetails of such optical sensors and other optical sensors for cell-basedassays have been described in detail in “Label-free cell-based assayswith optical biosensors in drug discovery”, by Ye Fang, in Assay andDrug Development Technologies, Vol 4, pp 583-595, 2006. Anoptical-sensor based system may include a device comprising opticalsensors in wells suitable for cell culture, an optical signalmeasurement/detection system such as optical CCD camera, anoptical-signal processing algorithm to process optical signals inshort-time resolution, such as millisecond resolution, to provide acardiomyocyte-beating dependent curve, and to quantify cell beating andto derive cell-beating parameters (such as calculating average rate ofbeats per unit time, average amplitude intensity in a unit time as wellas the average length of time between the beats) based on cellmorphology images.

In the preferred approach the system is an impedance-based cellmonitoring system. Most preferably, the system provides a device formonitoring cell-substrate impedance, an impedance analyzer capable ofimpedance measurements at millisecond time resolution, electroniccircuitry that can engage the device and selectively connect two or moresensors or electrode arrays of the device to the impedance analyzer anda software program that controls the electronic circuitry and recordsand analyzes data obtained from the impedance analyzer. By providing theimpedance based system with millisecond time resolution, beatingmeasurements from excitation-contraction coupling of cells can beefficiently monitored in millisecond time resolution. Thus the methodsprovided herein may be combined with impedance-based systems to identifyand evaluate changes in excitation-contraction events and shifts inbeating parameters discussed below, which may be used for highthroughput analysis of potential therapeutics. The skilled artisan willappreciate that millisecond time resolution measurements may be coupledwith longer term impedance monitoring, such as longer than seconds,hours or days. In some embodiments, long term impedance monitoring isperformed with intermittent periods of impedance monitoring atmillisecond time resolution. Suitable impedance monitoring systems aredescribed in detail in U.S. patent application Ser. No. 12/435,569,which is herein incorporated by reference in its entirety. A preferredelectrode array or configuration is also provided in FIGS. 1A and B.

The preferred device for monitoring substrate impedance includes anonconductive substrate having one or more individually addressableelectrode arrays or sensors fabricated thereon and one or more wells. Asurface of the substrate may be suitable for cell attachment, whereinthe cell attachment results in a detectable change in impedance betweenelectrodes within the array. Preferably, the nonconducting substrate isplanar, and is flat or approximately flat. The substrates may beconstructed from a variety of nonconductive materials known in thepresent art, including, but not limited to, silicon dioxide on silicon,silicon-on-insulator (SOI) wafer, glass (e.g., quartz glass, lead glassor borosilicate glass), sapphire, ceramics, polymer, fiber glass,plastics, e.g., polyimide (e.g. Kapton, polyimide film supplied byDuPont), polystyrene, polycarbonate, polyvinyl chloride, polyester,polypropylene and urea resin. Preferably, the substrate is biocompatiblewith excitable cells such as cardiomyocytes; however, materials that arenot biocompatible can be made biocompatible by coating with a suitablematerial, such as a biocompatible polymer or coating. Further,attachment or growth along the substrate or electrodes may be enhancedby pre-coating the substrate with a protein or compound that facilitatesattachment or growth. Such compounds may be chosen according totechniques known in the cellular biology arts; however, in someembodiments fibronectin is effective. Alternatively, the substrate maybe chemically modified to display reactive groups that enhance cellattachment, particularly ES cells or cardiomyocytes.

Preferably, each sensor or electrode array includes two or moreelectrode structures that are constructed to have dimensions and spacingsuch that they can, when connected to a signal source, operate as a unitto generate an electrical field in the region of spaces around theelectrode structures. Preferably the electric field is substantiallyuniform across the array. An electrode structure refers to a singleelectrode, particularly one with a complex structure. Specifically, anelectrode array includes two electrode structures, each of whichincludes multiple electrode elements, or substructures, which branchfrom the electrode structure. In preferred embodiments, the electrodestructures of each of the two or more electrode arrays of a device havesubstantially the same surface area.

Each of the two electrode structures of an electrode array is connectedto a separate connection pad that is preferably located at the edge ofthe substrate. Specifically, for each of the two or more electrodearrays of the device, preferably the first of the two electrodestructures is connected to one of the two or more connection pads, andthe second of the two electrode structures is connected to another ofthe two or more connection pads. Preferably, each array of a device isindividually addressed, meaning that the electrical traces andconnection pads of the arrays are configured such that an array can beconnected to an impedance analyzer in such a way that a measuringvoltage can be applied across a single array at a given time usingswitches (such as electronic switches).

Preferably, each electrode array of the device has an approximatelyuniform electrode resistance distribution across the entire array. By“uniform resistance distribution across the array” is meant that when ameasurement voltage is applied across the electrode structures of thearray, the electrode resistance at any given location of the array isapproximately equal to the electrode resistance at any other location onthe array. Preferably, the electrode resistance at a first location onan array of the device and the electrode resistance at a second locationon the same array do not differ by more than 30%. More preferably, theelectrode resistance at a first location on an array of the device andthe electrode resistance at a second location on the same array do notdiffer by more than 15%. Even more preferably, the electrode resistanceat a first location on an array of the device and a second location onthe same array do not differ by more than 5%. More preferably yet, theelectrode resistance at a first location on an array of the device and asecond location on the same array do not differ by more than 2%.

Preferred arrangements for electrode elements and gaps between theelectrodes and electrode buses in a given electrode array are used toallow all cells, no matter where they land and attach to the electrodesurfaces and to contribute similarly to the total impedance changemeasured for the electrode array. Thus, it is desirable to have similarelectric field strengths at any two locations within any given array ofthe device when a measurement voltage is applied to the electrode array.At any given location of the array, the field strength is related to thepotential difference between the nearest point on a first electrodestructure of the array and the nearest point on a second electrodestructure of the array. It is therefore desirable to have similarelectric potential drops across the electrode elements and across theelectrode buses of a given array. Based on this requirement, it ispreferred to have an approximately uniform electrode resistancedistribution across the whole array where the electrode resistance at alocation of interest is equal to the sum of the electrode resistancebetween the nearest point on a first electrode structure (that is thepoint on the first electrode structure nearest the location of interest)and a first connection pad connected to the first electrode structureand the electrode resistance between the nearest point on a secondelectrode structure (that is the point on the first electrode structurenearest the location of interest) and a second connection pad connectedto the second electrode structure.

Preferably, devices of the present invention are designed such that thearrays of the device have an approximately uniform distribution acrossthe whole array. This can be achieved, for example, by having electrodestructures and electrode buses of particular spacing and dimensions(lengths, widths, thicknesses and geometrical shapes) such that theresistance at any single location on the array is approximately equal tothe resistance at any single other location on the array. In mostembodiments, the electrode elements (or electrode structures) of a givenarray will have even spacing and be of similar thicknesses and widths,the electrode buses of a given array will be of similar thicknesses andwidths, and the electrode traces leading from a given array to aconnection pad will be of closely similar thicknesses and widths. Thus,in these preferred embodiments, an array is designed such that thelengths and geometrical shapes of electrode elements or structures, thelengths and geometrical shapes of electrode traces, and the lengths andgeometrical shapes of buses allow for approximately uniform electroderesistance distribution across the array.

In some preferred embodiments of impedance measurement devices,electrode structures comprise multiple electrode elements, and eachelectrode element connects directly to an electrode bus. Electrodeelements of a first electrode structure connect to a first electrodebus, and electrode elements of a second electrode structure connect to asecond electrode bus. In these embodiments, each of the two electrodebuses connects to a separate connection pad via an electrical trace.Although the resistances of the traces contribute to the resistance at alocation on the array, for any two locations on the array the traceconnections from the first bus to a first connection pad and from thesecond bus to a second connection pad are identical. Thus, in thesepreferred embodiments trace resistances do not need to be taken intoaccount in designing the geometry of the array to provide for uniformresistances across the array.

In preferred embodiments of the present invention, a device formonitoring cell-substrate impedance has two or more electrode arraysthat share a connection pad. Preferably one of the electrode structuresof at least one of the electrode arrays of the device is connected to aconnection pad that also connects to an electrode structure of at leastone other of the electrode arrays of the device. Preferably for at leasttwo arrays of the device, each of the two or more arrays has a firstelectrode structure connected to a connection pad that connects with anelectrode structure of at least one other electrode array, and each ofthe two or more arrays has a second electrode structure that connects toa connection pad that does not connect with any other electrodestructures or arrays of the device. Thus, in preferred designs of adevice there are at least two electrode arrays each of which has a firstelectrode structure that is connected to a common connection pad and asecond electrode structure that is connected to an independentconnection pad.

In some preferred embodiments of the present invention, each of theelectrode structures of an array is connected to an electrode bus thatis connected to one of the two or more connection pads of the device viaan electrically conductive trace. In preferred embodiments, each of thetwo electrode structures is connected to a single bus, such that eacharray connects to two buses, one for each electrode structure. In thisarrangement, each of the two buses connects to a separate connection padof the substrate.

The electrically conductive traces that connect a bus with a connectioncan be fabricated of any electrically conductive material. The tracescan be localized to the surface of the substrate, and can be optionallycovered with an insulating layer. Alternatively the traces can bedisposed in a second plane of the substrate. Description of arrangementsand design of electrically conductive traces on impedance measurementdevices can be found in U.S. Pat. No. 7,470,533, herein incorporated byreference for all disclosure on fabrication and design of electricallyconductive trace on substrates.

Appropriate electronic connection means such as metal clips engaged ontothe connection pads on the substrate and connectedprinted-circuit-boards can be used for leading the electronicconnections from the connection pads on the devices to externalelectronic circuitry (e.g. an impedance analyzer). Description of thedesign of cell-substrate impedance devices and their manufacture can befound in U.S. Pat. No. 7,470,533, herein incorporated by reference forall description and disclosure of the design, features, and manufactureof impedance device comprising electrode arrays.

Descriptions of electrode arrays used for impedance measurement thatapply to the devices of the present invention are also described in U.S.Pat. No. 7,470,533, herein incorporated by reference for all disclosurerelating to electrode arrays (or structural units), electrodestructures, electrode materials, electrode dimensions, and methods ofmanufacturing electrodes on substrates.

Preferred electrode arrays for devices of the present invention includearrays comprising two electrode structures, such as, for example, spiralelectrode arrays and interdigitated arrays. In some preferred devices ofthe present invention, electrode arrays are fabricated on a substrate,in which the arrays comprises two electrode structures, each of whichcomprises multiple circle-on-line electrode elements, in which theelectrode elements of one structure alternate with the electrodeelements of the opposite electrode structure. Electrode arrays may beprovided in configurations, such as interdigitated, circle-on-line,diamond-on-line, concentric, sinusoidal and castellated.

Preferably, the electrode elements (or electrode structures) of an arrayof the present device of the present invention are of approximatelyequal widths. Preferably the electrode elements (or electrodestructures) of an array of the present device of the present inventionare greater than 20 microns and less than 500 microns in width, morepreferably from about 50 to about 300 microns in width.

Preferably, the electrode elements (or electrode structures) of an arrayof the present device of the present invention are approximately evenlyspaced. Preferably, the gap between electrode elements (or electrodestructures) of an array of the present device of the present inventionis less than 100 microns and more than 5 microns in width, morepreferably from about 10 to about 80 microns in width.

Preferably, the device includes one or more fluid-impermeablereceptacles which serve as fluid containers or wells. Such receptaclesmay be reversibly or irreversibly attached to or formed within thesubstrate or portions thereof (such as, for example, wells formed as ina microtiter plate). In another example, the device of the presentinvention includes microelectrode strips reversibly or irreversiblyattached to plastic housings that have openings that correspond toelectrode structure units located on the microelectrode strips. Suitablefluid container materials comprise plastic, glass, or plastic coatedmaterials such as a ceramic, glass, metal, etc. Descriptions anddisclosure of devices that comprise fluid containers can be found inU.S. Pat. No. 7,470,533, herein incorporated by reference for alldisclosure of fluid containers and fluid container structures that canengage a substrate comprising electrodes for impedance measurements,including their dimensions, design, composition, and methods ofmanufacture.

In preferred embodiments, each electrode array on the substrate of adevice of the present invention is associated with a fluid-impermeablecontainer or receptacle, such as, for example, a well. Preferably, thedevice of the present invention is assembled to a bottomless, multiwellplastic plate or strip with a fluid tight seal. The device is assembledsuch that a single array of the substrate is at the bottom of areceptacle or well. Preferably, each array of a device is associatedwith a well of a multiwell plate. In some preferred embodiments, amultiwell device for cell-substrate impedance measurement has“non-array” wells that are attached to the substrate but not associatedwith arrays. Such wells can optionally be used for performingnon-impedance based assays, or for viewing cells microscopically.

The design and assembly of multiwell impedance measurement devices isdescribed in U.S. Pat. No. 7,470,533, and also in U.S. Pat. No.7,192,752, both herein incorporated by reference for disclosure ofmultiwell impedance measurement devices, including their design,composition, and manufacture. A device of the present inventionpreferably has between 2 and 1,536 wells and more preferably between 4and 384 wells. In some embodiments the device includes 6 wells, 16wells, 32 wells, 96 wells or 386 wells.

In some preferred embodiments, commercial tissue culture plates can beadapted to fit a device of the present invention. Bottomless plates mayalso be custom-made to preferred dimensions. Preferably, well diametersare from about 1 millimeter to about 20 millimeters, more preferablyfrom about 2 millimeters to about 8 millimeters at the bottom of thewell (the end disposed on the substrate). The wells can have a uniformdiameter or can taper toward the bottom so that the diameter of thecontainer at the end in contact with the substrate is smaller than thediameter of the opposing end.

In the system for monitoring impedance of beating cells the impedanceanalyzer engages connection pads of one or more multi-well devices tomeasure impedance. In one embodiment of the above system, the impedanceanalyzer is capable of measuring impedance between 0.1 ohm and 10⁵ ohmin frequency range of 1 Hz to 1 MHz. The impedance analyzer ispreferably capable of measuring both resistance and reactance(capacitive reactance and inductive reactance) components of theimpedance. In a preferred embodiment of the above system, the impedanceanalyzer is capable of measuring impedance between 1 ohm and 10³ ohm infrequency range of 1.00 Hz to 300 kHz.

In preferred embodiments the impedance analyzer is capable of impedancemeasurements at millisecond time resolution. The required or desiredtime resolution may vary depending on the excitation cycle of theexcitable cell. Excitable cells having shorter excitation cycles wouldtend to require faster time resolution. In some embodiments 500millisecond time resolution is sufficient, such that at least twoconsecutive impedance measurements are between about 300 millisecondsand about 500 milliseconds apart. In preferred embodiments, impedancemeasurement at millisecond time resolution includes at least twoconsecutive impedance measurements less than 100 milliseconds apart. Insome instances the at least two consecutive impedance measurements areless than 50 milliseconds or less than 40 milliseconds apart. In someinstances the at least two consecutive impedance measurements are lessthan 20 milliseconds apart. In some instances at least two consecutiveimpedance measurements are less than 10 milliseconds apart. In someinstances millisecond time resolution includes two consecutive impedancemeasurements between 1 millisecond and 5 milliseconds, between 5milliseconds and 10 milliseconds, between 10 milliseconds and 20milliseconds, between 20 milliseconds and 40 milliseconds, or between 40milliseconds and 50 milliseconds apart. In some instances millisecondtime resolution includes at least two consecutive impedance measurementsbetween 50 milliseconds and 100 milliseconds apart. In some instancesmillisecond time resolution includes at least two consecutive impedancemeasurements between 100 milliseconds and 150 milliseconds or between150 and 300 milliseconds apart.

With millisecond time resolution for impedance measurement, it becomespossible to resolve individual beating cycles of cardiomyocytes culturedon electrodes. Whilst theoretically one needs at least two data pointsfor each beating cycle, in practice more than 2 data points are neededfor each beating cycle. For example, if cells have a beating rate of 60beats per minute, i.e., one beat per second. It would be preferred tohave a time resolution of at least 200 milliseconds so that each beatingcycle consists of 5 data points. More preferably, the measurement timeresolution is 100 milliseconds. Still more preferably, the timeresolution is 50 milliseconds or less.

One skilled in the art will understand that the cell-substrate impedancemeasurement or monitoring system with millisecond time resolution can beused to efficiently and simultaneously perform multiple assays by usingcircuitry of the device station to digitally switch from recording frommeasuring impedance over an array in one well to measuring impedanceover an array in another well. Similarly, groups of wells may bemonitored simultaneously and switched between designated groups. In oneembodiment of the above system, the system under software control iscapable of completing an impedance measurement for an individual well ata single frequency within milliseconds, such as less than 100milliseconds, less than 40 milliseconds, less than 20 milliseconds, lessthan 10 milliseconds or between 1 millisecond and 40 milliseconds. Insome embodiments the user may choose the frequency of measurement formillisecond time resolution.

A multiple-well cell-substrate impedance measuring device in a system ofthe present invention can be any multiple-well cell-substrate impedancemeasuring device in which at least two of the multiple wells comprise anelectrode array at the bottom of the well, and in which at least two ofthe multiple wells comprise an electrode array are individuallyaddressed. In one embodiment of the above system, the multi-well devicetakes the form of a specialized microtiter plate which hasmicroelectronic sensor arrays integrated into the bottom of the wells.

A device used in a system of the present invention, when connected to animpedance analyzer, can measure differences in impedance values thatrelate to cell behavior. For example, a cell-substrate impedancemeasuring device used in a system of the present invention can measuredifferences in impedance values when cells are attached to the electrodearray and when cells are not attached to the electrode array, or candetect differences in impedance values when the number, type, activity,adhesiveness, or morphology of cells attached to theelectrode-comprising surface of the apparatus changes. Further, by usingmillisecond time resolution differences in impedance may be detected ormonitored that relate to excitation-contraction coupling, including thebeating of cardiomyocytes or stem cells differentiating intocardiomyocytes, and the signaling between neurological cells. Impedancemonitoring of the excitation cycle of excitable cells may be determinedand monitored before, during or after adding a test compound, which issuspected of affecting the excitation cycle. Thus, by monitoring theexcitation cycle of the excitable cell before, during or after adding atest compound the system provides data corresponding to the potentialaffect of the compound on the cardiovascular system, the heart, thenervous system, and the like. In some embodiments monitoring theexcitation cycle of the cell before, during or after adding a compoundprovides cardiotoxicity data useful in drug screening.

In some embodiments a device station or electromechanical apparatus orassembly capable of interfacing multiwell devices can include one ormore platforms or one or more slots for positioning one or moremultiwell devices. The one or more platforms or one or more slots cancomprise sockets, pins or other devices for electrically connecting thedevice to the device station. The device station or electromechanicalapparatus or assembly capable of interfacing multiwell devicespreferably can be positioned in a tissue culture incubator during cellimpedance measurement assays. It can be electrically connected to animpedance analyzer and computer that are preferably located outside thetissue culture incubator.

The device station or electromechanical apparatus or assembly capable ofinterfacing multiwell devices includes electronic circuitry that canconnect to the impedance monitoring device and an impedance analyzer andelectronic switches that can switch on and off connections to each ofthe two or more electrode arrays of the multiwell devices used in thesystem. The switches of the device station or electromechanicalapparatus or assembly capable of interfacing multiwell devices arecontrolled by a software program, each of which has been improved toprovide millisecond time resolution. The software program directs thedevice station to connect arrays of the device to an impedance analyzerand monitor impedance from one or more of the electrode arrays. Duringimpedance monitoring, the impedance analyzer can monitor impedance atone frequency or at more than one frequency. Preferably, impedancemonitoring is performed at more than one time point for a given assay,and preferably, impedance is monitored using at least two time points.The device station can connect individual arrays of a device to animpedance analyzer to monitor one, some, or all of the arrays of adevice for a measurement time point. In some preferred embodiments ofthe present invention, the device station software is programmable todirect impedance monitoring of any of the wells of the device thatcomprise arrays at chosen time intervals.

The software of the impedance monitoring system can also store anddisplay data. Data can be displayed on a screen, as printed data, orboth. Preferably the software can allow entry and display ofexperimental parameters, such as descriptive information including cellstypes, compound concentrations, time intervals monitored, etc. Further,since a plurality of beating parameters are obtained using the beatingmeasurements, software provides menus to select one or more of thebeating parameters for analysis.

The software, termed RTCA CARDIO SOFTWARE (ACEA Biosciences Inc., SanDiego, Calif.), also permits fast analysis of beating parameters. Thus,after obtaining impedance measurements the software can calculate ordetermine from the impedance measurement a plurality of beatingparameters such as beating rate, beating amplitude, rising time, fallingtime, beating period, IBD10, IBD50, IBD90, rising slope, falling slope,normalized beating rate, normalized beating amplitude, beating patternsimilarity and beating rhythm irregularity, and perform subsequentstatistics, such as average and standard deviation and further supplyIC50 or EC50 values for dose-response testing.

Determining Cell Index from Impedance or Optical Measurements

Although raw impedance values or raw values obtained from opticalsensors may be used as beating measurements in preferred embodiments theraw impedance values are converted to cell index values or delta cellindex values for comparison or further derivation into beatingparameters as discussed below. Information regarding how to calculate acell index, cell change index, normalized cell index, and delta cellindex may be found in U.S. patent application Ser. No. 12/435,569, U.S.patent application Ser. No. 11/903,454, and U.S. Pat. No. 7,470,533, thecontents of which are herein incorporated by reference with respect tothe cell index, cell index number, cell change index, and cell changeindex number. However a briefly summary is provided.

The cell index obtained for a given well reflects: 1) how many cells areattached to the electrode surfaces in this well, and 2) how well cellsare attached to the electrode surfaces in the well. In this case, a zeroor near-zero “cell index or cell number index” indicates that no cellsor very small number of cells are present on or attached to theelectrode surfaces. In other words, if no cells are present on theelectrodes, or if the cells are not well-attached onto the electrodesthe cell index equals 0. A higher value of “cell index” or “cell numberindex” indicates that, for the same type of the cells and cells undersimilar physiological conditions, more cells are attached to theelectrode surfaces. Thus cell index is a quantitative measure of cellnumber present in a well. A higher value of “cell index” may alsoindicate that, for the same type of the cells and the same number of thecells, cells are attached better (for example, cells spread out more, orcell adhesion to the electrode surfaces is stronger) on the electrodesurfaces.

Non-limiting examples for determining cell index follow. Cell index canbe calculated by: at each measured frequency, calculating the resistanceratio by dividing the measured resistance (when cells are attached tothe electrodes) by the baseline resistance; finding or determining themaximum value in the resistance ratio over the frequency spectrum; andsubtracting one from the maximum value in the resistance ratio. Inanother variation, cell index is determined by: at each measuredfrequency, calculating the resistance ratio by dividing the measuredresistance (when cells are attached to the electrodes) to the baselineresistance; finding or determining the maximum value in the resistanceratio over the frequency spectrum; and taking a log-value (e.g., basedon 10 or e=2.718) of the maximum value in the resistance ratio. Inanother variation, cell index is determined by: at each measuredfrequency, calculating the reactance ratio by dividing the measuredreactance (when cells are attached to the electrodes) to the baselinereactance; finding or determining the maximum value in the reactanceratio over the frequency spectrum; and subtracting one from the maximumvalue in the resistance ratio. In still another variation, cell indexcan be calculated by: at each measured frequency, calculating theresistance ratio by dividing the measured resistance (when cells areattached to the electrodes) to the baseline resistance; then calculatingthe relative change in resistance in each measured frequency bysubtracting one from the resistance ratio; and then integrating all therelative-change value.

It is worthwhile to point out that it is not necessary to derive such a“cell index” for utilizing the impedance information for monitoring cellconditions over the electrodes. Actually, one may choose to directly useimpedance values (e.g., at a single fixed frequency; or at a maximumrelative-change frequency, or at multiple frequencies) as an indicatorof cell conditions.

A “normalized cell index” at a given time point is calculated bydividing the cell index at the time point by the cell index at areference time point. Thus, the normalized cell index is 1 at thereference time point. Normalized cell index is cell index normalizedagainst cell index at a particular time point. In most cases in thepresent applications, normalized cell index is derived as normalizedrelative to the time point immediately before a compound addition ortreatment. Thus, normalized cell index at such time point (immediatelybefore compound addition) is always unit one for all wells. One possiblebenefit for using such normalized cell index is to remove the effectfrom difference in cell number in different wells. A well having morecells may produce a larger impedance response following compoundtreatment. Using normalized cell index, it helps to remove suchvariations caused by different cell numbers.

A “delta cell index” at a given time point is calculated by subtractingthe cell index at a standard time point from the cell index at the giventime point. Thus, the delta cell index is the absolute change in thecell index from an initial time (the standard time point) to themeasurement time.

The time-dependent cellular response (including cardiotoxicity response)may be analyzed by deriving parameters that directly reflect the changesin cell status. For example, time dependent cellular response may beanalyzed by calculating the slope of change in the measured impedanceresponses (that is equivalent to the first order derivative of theimpedance response with respect to time, impedance response here can bemeasured impedance data or derived values such as cell index, normalizedcell index or delta cell index). In another example, the time-dependentcellular responses (including cardiotoxic responses) may be analyzed fortheir higher order derivatives with respect to time. Such high orderderivatives may provide additional information as for how cellsresponding to different compounds and as for the mechanisms of compoundaction.

The use of cell index together with millisecond time resolutionimpedance monitoring is demonstrated in FIGS. 2-6, which depict highresolution images of the cardiomyocyte beating cycle and patternshifting in response to administration of cardiotoxic compounds. Whilecell index permits graphically depicting the beating cycle, still moredetailed analysis of beating parameters reveals improvements tocardiomyocyte population analysis.

Beating Parameters Derived from Millisecond Time Resolution Measurementsor Cell Index

While impedance measurements, optical measurements and cell index valuescan provide valuable information about a cell population, a variety ofbeating parameters are established which further assist in the analysisof a beating cardiomyocyte, a beating cell or cell populationdifferentiating into a beating cell population. Further, the beatingparameters permit comparisons before and after treatment with acompound, typically a test compound, to assess its effect or predictedeffect on a cardiomyocyte cell population and the like. As such, thebeating parameters may be used to establish or confirm safety of acompound or provide further insight as to the potential mechanism ofaction of a compound, such as its effect on stem cell differentiation toor away from a cardiomyocyte cell type or characteristic. Further, byproviding a compound at various concentrations its dose response can bestudied. The below beating parameters have been found useful inassessing potential effects on cardiomyocytes and thus each alone or incombination can be used to assess potential risk of compound basedtherapies.

In one approach beating measurements are used to determine beating cyclepeaks associated with a cell. Beating itself corresponds to theexcitation-contraction coupling of the cells. Turning to FIG. 7,beatings are defined as a sequence of Positive Peaks (+P as labeled) andNegative Peaks (−P as labeled). The value of these Positive Peaks andNegative Peaks and the corresponding time periods determine the beatingcharacteristics, which reveal the status of the cardiomyocytepopulation. For example, in FIG. 7, a Positive Peak may correspond tothe contraction of cardiomyocytes, whilst the return of measurementvalues to baseline and to negative peak may correspond to the relaxationof cardiomyocytes.

As an example, time dependent impedance values or cell index values fora well are analyzed by deriving their first order derivatives and secondorder derivatives using numerical methods. The beating cycle peaks arethose data points where the first order derivatives of impedance valuesor cell index values are zero or close to zero in absolute value. If thebeating cycle peak is a positive peak (i.e. peak corresponds to amaximum value in measured impedance or cell index over the beatingcycle), then the peak would correspond to data points where the secondorder derivatives of the impedance values or cell index values arenegative and where the first order derivatives of the impedance valuesor cell index values are zero or close to zero in absolute value. If thebeating cycle peak is a negative peak (i.e. peak corresponds to aminimum value in measured impedance or cell index over the beatingcycle), then the peak would correspond to the data points where thesecond order derivatives of the impedance values or cell index valuesare positive and where the first order derivatives of the impedancevalues or cell index values are zero or close to zero in absolute value.

In yet another approach, the method for searching for and identifying“positive peaks” and “negative peaks” may involve the use andmodification of various mathematical algorithms, e.g., theDouglas-Peucker algorithm. The Douglas-Peucker algorithm is an algorithmfor reducing the number of points in a curve that is approximated by aseries of points. Based on the required maximum distance between on theoriginal curves and on the simplified curves, the Douglas-Peuckeralgorithm could also be adopted to identify positive peaks and negativepeaks in time-dependent data point series for impedance values and/orcell index vales.

In another approach, a method of determining a beating cycle peak is tosearch for the data point where the trend of the data changes directionfrom “increasing” to “decreasing” with time (for a positive peak), orfrom “decreasing” to “increasing” (for a negative peak). After theidentification of the beating cycle peaks, the impedance or cell indexvalues at such peak time points provide the magnitude or amplitude ofthe beating cycle peaks.

After determining the beating cycle peaks, various methods can be usedto calculate the beating rate. A beating rate parameter is generallyprovided as beatings per minute. In a positive peak counting approach,the number of positive peaks is determined over a given time intervaland converted to the desired unit, preferably beats per minute.Similarly, in a negative peak counting approach the number of negativepeaks is determined over given time interval and converted to thedesired unit. As an example, if there are 2 peaks in a one secondinterval, then the beating rate would be 2 beats per second, or 120beats per minute. In still another approach, beating rate is calculatedby determining the time period between a series of two or more positivepeaks or between a series of two or more negative peaks. That is, inthis approach a unit of time (e.g., 1 minute) is divided by the timeperiod between two adjacent peaks. For example, if two adjacent peaksare separated by 500 milliseconds, then the beating rate would be 120beats per minute. In a time interval comprising multiple positive ornegative peaks, the beating rate could be determined by the followingmethod. Take positive peaks as an example, the time periods betweenevery pairs of two adjacent positive peaks are calculated. Then thebeating rate could be calculated in two ways. The first method is todivide a unit of time (e.g., 1 minute) by the average of the timeperiods between all two-adjacent positive peaks in the given timeinterval. The second method is to calculate the corresponding beatingrates based on each pair of two adjacent positive peaks and then toaverage of the adjacent-peaks-derived beating rates.

To further assist in comparison, beating rates can also be normalized.Determining a normalized beating rate is achieved by dividing thebeating rate at a selected data analysis time by a beating rate at anormalization time. Thus a beating rate identical to that at thenormalization time would be defined as 1. Normalizing beating rates canprovide a more clear indication of whether and to what degree a changein beating rate occurs. For example, normalization time corresponds tothe time point of measurement immediately prior to a compound treatmentof the cardiomyocytes. Thus, normalized beating rates could provideclear information as for what the effect of the compound has on thebeating rates. A normalized beating rate close to 1 or equal to 1 meansthat the compound does not have much effect on the beating rate, Anormalized beating rate smaller than 1 means that the compound mayresult in reduction in the beating rates of cardiomyocytes. A normalizedbeating rate larger than 1 means that the compound may cause an increasein the beating rates of cardiomyocytes. Normalized beating rates couldbe derived for beating rates calculated using different methods such aspeak-counting derived beating rates and beating peak periods derivedbeating rates.

Beating amplitude is a parameter used in some embodiments to describe orcorrespond to the intensity of the peak, which may reflect the extent ofcontraction or relaxation of cardiomyocytes during a beating cycle.Determining beating amplitude can involve a whole peak approach, whichcould be determined by the difference between a negative peak and thefollowing positive peak as shown in FIG. 7. For example, in FIG. 7 thebeating amplitude is shown as the difference in cell index between aNegative Peak to the following adjacent Positive Peak (Amp-1, Amp-2,Amp-3, . . . , Amp-m). In another approach, beating amplitude for apositive peak is the difference between a determined baseline to apositive peak. In still another approach beating amplitude for anegative peak is the difference between a determined baseline to anegative peak. An exemplary baseline is shown in FIG. 7.

Thus, for a single beating cycle, one could define or identify differenttypes of amplitude (or an amplitude) of the beating-cycle peaks,including the amplitude of positive peak, the amplitude of negative peakand the amplitude of the whole peak in a cycle. From the measured datapoint series, a baseline value, which may theoretically correspond tothe value when the cardiomyocytes are at their fully relaxation status,could be determined or identified from the measured data values in atime series. The amplitude of a positive peak is the impedance value orcell index value or other measurement value at the positive-peak timepoint subtracted by the baseline value. The amplitude of a negative peakis the impedance value or cell index value or other measurement value atthe negative-peak time point subtracted by the baseline value. Theamplitude of whole peak is the difference in the impedance value or cellindex value or other measurement value between positive-peak time pointand negative-peak time point.

Whilst the above paragraph discusses different types of the amplitudesof a single beating cycle, for a time period including multiple beatingcycles, one could determine the average and standard deviations (orstandard errors) of the positive-peak amplitude, the negative-peakamplitude and whole-peak amplitude.

Beating amplitude can also be normalized as a normalized amplitude. Anormalized amplitude is the amplitude at a selected data analysis timedivided by the amplitude at the normalization time point. A beatingamplitude identical to that at the normalization time would be definedas 1. Thus, the normalized amplitude reveals differences, such as anincrease or decrease in the amplitude or intensity of a beat compared toa referenced amplitude. For example, normalization time corresponds tothe time point of measurement immediately prior to a compound treatmentof the cardiomyocytes. Thus, normalized beating amplitudes could provideclear information as for what the effect of the compound has on thebeating amplitudes. A normalized beating amplitude close to 1 or equalto 1 means that the compound does not have much effect on the beatingamplitude. A normalized beating amplitude smaller than 1 means that thecompound may result in reduction in the beating amplitudes ofcardiomyocytes. A normalized beating amplitude larger than 1 means thatthe compound may cause an increase in the beating rates ofcardiomyocytes.

Normalized beating amplitude could be derived for all three types ofbeating amplitudes, i.e. positive-peak based amplitude, negative-peakbased amplitude and whole-peak amplitude.

In some instances, it is more useful to consider a beating amplitudethat is less than the difference between the positive peak and negativepeak or baseline. For example, in may be desirable to consider a portionof the amplitude, such as a 10% amplitude, 20% amplitude, 50% amplitude,80% amplitude, 90% amplitude and the like. This may be particularlypreferred when assessing other parameters together with beatingamplitude such as when considering a rising slope or an IBD10, IBD50,IBD90 and the like.

Rising time T_(r) is a parameter which provides the amount of time totravel the rising slope between the negative peak and the positive peak(or between the baseline and the positive peak). Typically, rising timeis provided as an average over many beatings and is converted to time inthe unit of seconds for analysis or comparison. In some embodimentsrising time is calculated as the time needed to reach a positive peak ormaximum amplitude from a negative peak or a baseline. Referring to FIG.8 as an example, in other instances, rising time T_(r) is calculatedbetween data points positioned below the positive peak and above thenegative peak (or below the positive peak and above the baseline). Thatis, since the slope of the beating curve changes dramatically at thepeaks, it is often preferred to consider the rising time between 20%amplitude and 80% amplitude for comparison. Thus, when determiningrising time it may be necessary to first determine the beating amplitudethen determine suitable comparison points such as 20% amplitude, 50%amplitude, 80% amplitude and the like. By one example as illustrated inFIG. 8, rising slope can be calculated by the dividing the cell indexchange from 20% amplitude to 80% amplitude by the time it takes asfollows:

Rising Slope=(Amp₈₀−Amp₂₀)/T _(r)

Depending on specific application, it is possible that we may defineother rising time and/or rising slopes, using different percentageamplitude points. For example, rising slope may be defined as:

Rising Slope=(Amp₉₀−Amp₁₀)/T _(r)

Falling time T_(f) is a beating parameter which provides the amount oftime to travel the falling slope between a positive peak or a point ofmaximum amplitude to a negative peak or a baseline. Falling time T_(f)can be provided as an average over many beatings and is generallyconverted to time in the unit of seconds for analysis or comparison. Insome embodiments falling time T_(f) is calculated as the time needed toreach a negative peak or baseline from a positive peak; however,referring again to FIG. 8 as an example, in other instances, fallingtime T_(f) is calculated between data points positioned below thepositive peak and above the negative peak. That is, since the slope ofthe beating curve changes dramatically at the peaks, it is oftenpreferred to consider the falling time between 80% amplitude (or 90%amplitude) and 20% amplitude (or 10% amplitude) for comparison. Thus,when determining falling time it may be necessary to first determine thebeating amplitude then determine suitable comparison points such as 10%amplitude, 20% amplitude, 50% amplitude, 80% amplitude, 90% amplitudeand the like. By way of example, falling slope can be calculated bydividing the cell index change from 80% amplitude to 20% amplitude bythe time it takes as follows:

Falling Slope=(Amp₈₀−Amp₂₀)/T _(r)

Depending on specific application, it is possible that we may defineother rising time and/or rising slopes, using different percentageamplitude points. For example, falling slope may be defined as:

Falling Slope=(Amp₉₀−Amp₁₀)/T _(r).

IBD50 provides the time window between time points where the beatingsignals attains 50% amplitude. IBD50 is particularly useful whenstudying the effect of the compounds on the beating cycle ofcardiomyocytes. For example, if a compound, through various mechanisms,results in prolongation of contraction phase of the beating cycle of thecardiomyocytes, then IBD50 derived from the beating cycle waveform maybe increased as a result of the treatment of cardiomyocytes with thiscompound. In another example, if a compound results in certainpro-arrhythmia effects in cardiomyocytes (see FIG. 3 as an example whereE4031 induced arrhythmia effects), then IBD50 derived from the beatingcycle waveform may also be significantly altered. Similarly, other timewindows can be used instead to assess similar pro-arrhythmia effects atdifferent percentage of the amplitude such as 10% amplitude and 90%amplitude to give IBD10 and IBD90. Time between following IBD10, IBD50or IBD90 measurements are designated as T_(IBD10), T_(IBD50), andT_(IBD90). An exemplary T_(IBD50) parameter is shown in FIG. 8.

Beating period (also referred to as “beating cycle”) is a parameterwhich provides the time period between two positive peaks, two negativepeaks or can be the time period between a positive peak and a negativepeak. The beating period can be used to identify changes in beating rateor can be used as a defined period for comparison of other parameters,such as differences in amplitude, rising time, falling time and thelike. In FIG. 7, within one Sweep Duration, the number of Positive Peaksis m (+P1, +P2, +P3, . . . , +Pm) and the number of Negative Peaks is n(−P1, −P2, −P3, . . . , −Pn). The time between two adjacent individualPositive Peaks (or/and two adjacent individual Negative Peaks) isdefined as beating period. For example, the beating period based on thePositive Peaks is T_(+P1), T_(+P2), T_(+P(m−1)) and the beating periodbased on the Negative Peaks is T_(−P1), T_(−P2), . . . , T_(−P(n−1)).

Rising slope is a parameter corresponding to the slope that occursduring a specified time period when the measured impedance values orcell index values or other measurement/derived values increase withtime. That is, the rising slope is a slope between a negative peak andan adjacent baseline point (which is after the negative peak in time),or between certain baseline point and an adjacent positive peak (whichis after the baseline point in time), or between a negative peak and itsimmediately adjacent positive peak (which is after the negative peak intime). For a single beat, one could determine rising slopes based ondifferent definitions as described in the previous sentence. The risingslope may be an average between multiple slopes across multiple beats.

Falling slope is a parameter that corresponds to the slope that occursduring a specified time period when the measured impedance values orcell index values or other measurement/derived values decrease withtime. Thus, the falling slope is a slope between a positive and anadjacent baseline point (which is after the positive peak in time), orbetween certain baseline point and a negative peak (which is after thebaseline point in time), or between a positive peak and its immediatelyadjacent negative peak (which is after the positive peak in time). For asingle beat, one could determine falling slopes based on differentdefinitions as described in the previous sentence. The falling slope maybe an average between multiple slopes across multiple beats.

Beating pattern similarity is a parameter derived to quantify the degreeof the similarity between the beating waveforms between two differenttime intervals. For any given time interval, the beating pattern isshown as the beating curves comprised of a number of measurement values(impedance values, cell index values or other values) across a number oftime points during the time interval. Beating patterns at two timeintervals may be compared numerically, such as by comparison betweendetermined parameters for the beating curves at these two time intervalsor patterns may be compared through the comparison of the beatingcurves. When comparing curves it may desirable to align curves to matchan initial positive peak or initial negative peak. Aligning curves mayalso use a variety of curve algorithms, which identify distances orshifts between curves.

In one embodiment, the beating pattern similarity is derived as aparameter to compare the determined parameters for the beating curves attwo time intervals. For example, one may compare the beating rates BR₁and BR₂ at the two time intervals. An example of the beating patternsimilarity is given as:

Beating pattern similarity=(2*BR ₁ *BR ₂)/(BR ₁ *BR ₁ +BR ₂ *BR ₂)

With this above example, the beating pattern similarity is one (thehighest value) when the beating rates at the two time intervals are thesame. When the beatings rates differ at two time intervals, the beatingpattern similarity would be less than 1. The more the beating ratesdiffer, the smaller the beating pattern similarity value.

In a preferred embodiment, however, the beating pattern similarity isderived as a parameter to directly compare the beating curves at the twotime intervals. The idea of the beating pattern similarity shouldpossess such properties that the value for beating pattern similarity islarge when the two beating curves are similar, and the value for beatingpattern similarity is small when the two beating curves are not similar.There are multiple methods for deriving such beating pattern similarityvalues.

In one method, as briefly mentioned above, for comparing the beatingcurves at two time intervals (assuming the same measurement timeresolutions for the measured data points), it may desirable to aligncurves to match an initial positive peak or initial negative peak. Afteraligning the initial peaks, an “AND” operation is performed on the timepoints for the two beating curves so that the overlapping time points onthe two beating curves are kept whilst non-overlapping time points oneither one of the beating curves are discarded. Thus, the remaining,overlapping data points on the two beating curves are of the same numberand it is possible to readily define a distance to describe whether thetwo beating curves are similar. For example, the beating patternsimilarity could be the correlation coefficient between the two dataseries in the remaining portions of the two beating curves. Clearly, themore similar the two curves, the larger the correlation coefficient(i.e., the larger the beating pattern similarity value is). In anotherexample, the beating pattern similarity could simply be certainmathematically-defined-distance (e.g. Euclidean distance) between twodata series in the remaining portion of the two beating curves. Notethat if the measurement time resolutions differ between the measureddata points, additional time points may be artificially inserted intothe beating curves with missing time points after mathematicallyinterpolation of the values for such added time points based on othermeasured data points. With this operation, the two beating curves wouldhave the same time resolutions.

In another method for comparing the beating curves at two time intervals(again, assuming the same measurement time resolutions for the measureddata points), one would take the beating curve (out of the two) with theshorter time duration. If the time-shorter beating curve comprises morethan half of the data points of the other beating curve, then some lastdata points from the shorter beating curve are removed to form a“base-curve” so that the number of the remaining data points in theshorter beating curve is half of the number of the data points in theother beating curve. Then a number of correlation coefficients would bedetermined where each correlation coefficient corresponds to thebase-curve aligned to one continuous segment (comprising of the samedata point number as the base-curve) of the other beating curve. Forexample, the first correlation coefficient is determined between thedata series of the base curve and the data series of first half of theother beating curve (starting from the first data point). The secondcorrelation coefficient is determined between the data series of thebase curve and the data series from the other beating curve withstarting point being the second data point. The last correlationcoefficient is determined between the data series of the base curve andthe data series from the second half of the other beating curve endingwith the last data point. Finally, the beating pattern similarity isdetermined as the maximum value of all the correlation coefficients.

There may be other methods or algorithms that could be used for derivingbeating pattern similarities. Beating pattern similarity could be usedto analyze the effect of a compound on the beating pattern ofcardiomyocytes. The beating curves from two time intervals are compared.For analyzing the effect of a compound, one time interval corresponds tothe time period before compound treatment whilst the other time intervalcorresponds to the time period after compound treatment. The beatingpattern similarity has an advantage over other parameters in comparingcompound's effect on the cardiomyocytes. The advantage is that it couldinclude or summarize all the effects due to the compound, i.e. theeffects on the beating rates, beating waveform shapes or beatingamplitudes etc could all be included into the single parameter of thebeating pattern similarity.

Beating rhythm irregularity (BRI) is a parameter which identifieschanges in beating rate or changes between peak periods for a beatingcurve over a time interval. Beating rhythm irregularity is also referredto as a beating rate irregularity index. If the beating rate or thebeating peak period does not change with time, then the beating rhythmis regular and the parameter of the beating-rhythm-irregularity shouldbe small, i.e. being zero or close to zero. On the other hand, if thebeating rate or beating period does change with time, then beatingrhythm is irregular and the parameter of the beating rhythm irregularityshould have a large value. As one requirement, the parameter of thebeating rhythm irregularity should be able to identify the arrhythmicbeating of cardiomyocytes. Thus, the beating-rhythm-irregularity shouldattain a large value for the beating curves of cardiomyocytes if thecardiomyocytes exhibit arrhythmic beating. There are multiple methodsfor calculating the beating rhythm irregularity for a beating curve overa time interval. For example, the positive peak periods foreach-adjacent-positive-peak-pair are calculated for the beating curve inthe given time interval. Then the average and standard deviation of suchmultiple positive peak periods are calculated. The beating rhythmirregularity can be calculated by dividing the standard deviation of thepositive peak periods by the average. In another example, the negativepeak periods for each adjacent negative peak pair are calculated for thebeating curve in the given time interval. Then the average and standarddeviation of such multiple negative peak periods are calculated. Thebeating rhythm irregularity can be calculated by dividing the standarddeviation of the negative peak periods by the average.

When the cardiomyocytes exhibit irregular beating, the beating curvesmay comprise some regular beating peaks (positive or negative) withregular amplitudes and some irregular beating peaks with somewhatsmaller (/or larger) amplitudes or with somewhat different beatingwaveforms (e.g., the impedance value or cell index value or othermeasurement value does not return to baseline level after a beatingpeak). Thus, number or presence of the irregular positive (or negative)beating peaks could be used as an indicator for beating rhythmirregularity. Such regular and irregular beats can be determined and theratio between the irregular and the regular beats, i.e. irregular toregular beats ratio, can be used to assess the pro-arrhythmia effects ofthe test compound. If there are no pro-arrhythmia effects, such ratioshould be very small and close to zero.

The skilled artisan will appreciate compounds may be added tocardiomyocyte populations to test for potential changes or effects inbeating parameters. Changes may include an increase or decrease in atleast one of the beating parameters. The change may include an increasein beating rhythm irregularity if the compound causes an irregularbeating in cardiomyocytes. If a compound results in a significant effecton the beating of cardiomyocytes, then beating pattern similaritybetween the beating curves before and after the compound treatment maybe small.

In some instances beating measurements are continually monitored and abeating parameter is calculated for a single beating cycle within a timeperiod for comparison. For example, the calculation for a beatingparameter such as an amplitude can be performed for a single beatingcycle. Further, a beating parameter from a single beating cycle (i.e.single beating peak) may provide a suitable control for later determinedbeating parameters. Due to the fact that single beating cycle may take ashort time to complete, beating parameter for a single beating cycle(i.e. single beating peak) is sometimes referred as beating parameter ata single time point.

Frequently, it may be desirable analyze one or more parameters within asingle beating period (i.e. for a single beating cycle). From a singlebeating cycle (single beating period) a variety of beating parameterscan be assessed including beating amplitude, rising or falling time,rising and falling slope and IBD50 and the like. Consideration within abeating period may also be particularly useful for use as an initialbeating period before the addition of a test compound to establishcontrol beating data for later comparison. The single beating periodapproach may also be of interest if an irregularity is detected, such asan irregular positive peak, negative peak, slope between peaks and thelike. For instance, an irregularity may be temporal and thus decay overtime, which if limited to studying across multiple beating periods couldbe averaged out and thus not be identified as statistically significant.Thus, if such an irregularity is identified, analysis of thecorresponding beating period may reveal significant differences comparedto control. Still further, analysis of the single beating period mayreveal a correlation to another change or shift in beating parameter notapparent through multi-beating period analysis.

In another approach one or more of the selected parameters aredetermined or calculated across a time period that includes multiplebeating periods (i.e. multiple beating cycles). One or more parameterscan be determined for each of the desired multiple beating periods. Thisapproach may be used to monitor consistency over time or as a continuousscanning technique to identify potential periods of irregularity forfurther single beating period analysis. The approach may also be used todevelop average values for comparison to test compounds.

While the methods permit the study of cardiomyocyte beating itselfincluding, changes in beating in response to cardiomyocyte or stem celldifferentiation and the like, the methods are also useful to assess theeffect of one or more test compounds on a cardiomyocyte cell population.Such assays may help predict potential cardiotoxic effects of compounds,effect on cell differentiation or growth and the like. The skilledartisan will appreciate parameters for cell populations treated withtest compounds may be compared to control treated populations, such asvehicle control, and the resulting parameters compared to assess fordifferences. Differences in beating parameters may be indicative ofcardiotoxicity or other effects.

In another embodiment, a dose response curve (DRC) of a test compound isdetermined. A dose response curve reveals changes to beating parametersin response to difference in concentrations of test compound.Preferably, selected parameters are calculated from beating measurementsthat are measured from wells having different concentrations of the sametest compound for a period of time where beating signals are continuous.Preferably, for each concentration, one value is calculated for theselected parameter for certain time points after addition of testcompound. Then a concentration dependent dose response curve of theselected parameter is fitted to a non-linear, sigmoidal-dose-responseequation to derive EC50 (or IC50) values. An example of a sigmoidaldose-response curve is as follows:

Y=Bottom+(Top−Bottom)/(1+10̂(Log EC₅₀ −X))

An example of a sigmoidal dose-response with variable slop is asfollows:

Y=Bottom+(Top−Bottom)/(1+10̂((Log EC₅₀ −X)*Hill Slope))

The derived IC50/EC50 values for different compounds could be used topredict, analyze, or compare the different compounds' cardiotoxicity ordifferent compounds' effect on beating of cardiomyocytes. Like IC50 orEC50 derived from other assays, a compound with lower IC50/EC50 valuesmay indicate that the compound is more potent in inducingcardiotocixicity effect or causing an effect on beating of thecardiomyocytes than the compound with higher IC50/EC50 values.

To further demonstrate the use of the above parameters, modulators ofion channel and non-ion channel proteins and targets as well asmodulators of neuro-hormonal machinery were tested in both time anddose-dependent manner (see for example FIGS. 3A-C and FIGS. 4A-C). Usingvarious parameters such as beating rate, amplitude and IBD50, we haveconfirmed that the half maximal concentrations obtained for thedifferent compounds are within the sensitivity range of patch clamprecording and other electrophysiological methodologies (data not shown).Importantly, we have also shown that certain classes of compounds suchas blebbistatin, which serve to decouple excitation from contraction,can be missed by electrophysiological readouts but can be detected bythe impedance-based measurement of cardiomyocyte beating. Theseobservations demonstrate that impedance-based assay system can detectmodulation of ion-channel and non-ion channel targets affecting bothexcitation and contraction of cardiomyocytes.

Also demonstrated is that a number of drugs that have been shown toinduce ventricular arrhythmia in the clinic and subsequently withdrawnfrom the market display reproducible impedance-based signature beatingprofiles in a time and dose-dependent manner (FIGS. 13A-B and FIG. 15).These signature beating profiles are qualitatively similar to earlyafter depolarization (EAD) phenomenon that is observed by manual patchclamp recording of cardiomyocytes after exposure to compounds and drugsthat inhibit ERG channel activity and consequently I_(kr) current(Fermini et al., 2003). While the appearance and mechanism of EADs arediverse, it is generally agreed that calcium homeostasis which caninfluence contraction plays an important role in various forms of EADs(Volders et al., 2000). It is thought that drug-induced block in I_(kr)current can delay repolarization leading to delayed inactivation ofcalcium channels and consequently, the resulting late inflow of calciumcontributes to emergence of EADs (Fermini et al., 2003). It is alsoimportant to mention that manifestation of arrhythmia by mechanismsother than ERG block and QT prolongation cannot be discounted. Forexample, it has been shown that certain compounds which shorten both APDand QT interval can also cause arrhythmia (Lu et al., 2008). While itremains to be shown whether such drugs can also induce characteristicEAD-like profiles in the assay system described here, it underscores theneed for implementation of an assay system which can assess theintegrated response of ion channel and non-ion channel targets tocapture the full range of drug responses.

While the cardiotoxic side effect of most drugs is primarily viewed as afunction of the concentration of the drug and its possible adverseinteraction with other compounds, it must be emphasized that thetime-dependent response of cardiomyocyte to a given concentrationexposure is also an important parameter. This point is especiallyrelevant for cardiac function where time-dependent heart ratevariability or dynamics of periodicity could be a key determinant ofproarrhythmic potential (Bass et al., 2008). Furthermore, an increasingnumber of drugs are found to inhibit hERG function by dual mechanisms ofshort-term channel block and long term hERG trafficking defects thatoperate over different time and concentration scales (van der Heyden etal., 2008). The non-invasive nature of the impedance readout allows formonitoring of cardiomyocyte response from millisecond time frame tominutes, hours and days in real-time and therefore well suited tocapture time series data for these complex responses. The utility ofthis feature was demonstrated with respect to treatment of mouseembryoninc stem cell derived cardiomyocytes (mESCC) with both pentmidineand doxorubicin (FIGS. 14A-C). Pentmidine, a hERG trafficking inhibitorassociated with TdP in the clinic had a major impact on beating rate andbeat duration that was elicited about 900 min after initial exposure(Kuryshev et al., 2005). Standard manual patch clamp techniques orplanar patch clamp techniques, while the golden standard, and mostlikely would have missed this effect because action potential recordingsare typically performed within the first hour after compound exposure.Doxorubicin, an anthracycline affected both the beating rate andperiodicity of beating while causing progressive and dose-dependentdecrease in overall impedance signal of the cells (within 24 hours aftercompound exposure) most likely due to loss of viability (FIGS. 14A andB). Therefore, the ability to simultaneously capture the dynamicity ofbeating rate changes coupled with overall changes in impedance toreflect the global compound effect on cell health within the same assaycan provide additional information regarding mechanism of toxicity.

EXAMPLES Example 1: Detection of Changes in Cardiomyoctye Beating inResponse to Administration of Pharmacologically Active Agents

Cell culture. Mouse ES cell-derived cardiomyocytes (Cor.At) wereobtained from Axiogenesis (Cologne, Germany, catalogue numberXCAC-1010E, Lonza Cologne). The cells were kept in liquid nitrogen untilthawed and cultured according to protocol provided by Axiogenesis withslight modifications. Briefly, each well of the E-PLATE (ACEABiosciences Inc., San Diego, Calif.) was coated with 50 μl of a 1:100diluted fibronectin (FN) solution (F1114, Sigma-Aldrich, USA) andincubated at 4° C. over night. Subsequent to removal of FN, the wellswere washed with PBS and followed by cell seeding. The cells were thawedat 37° C. in a waterbath, transferred to 15 mL conical tube containing 9ml fresh Cor.At complete culture medium (XCAM-250E, Lonza Cologne,Germany), centrifuged at 100 g for 5 minutes and the medium was replacedwith small volume of fresh Cor.At complete culture medium containingpuromyocin at final concentration of 10 μg/ml. The cells were countedand the percentage of viable cells determined by trypan blue exclusionmethod.

Monitoring of cardiomyoctye attachment and contraction. About40000-60000 viable cells were seeded per well of a 96 well E-PLATE (ACEABiosciences Inc., San Diego, Calif.) and the cells were monitored usingthe xCELLigence RTCA Cardio system (Roche Applied Science and ACEABiosciences). Cell culture medium was replaced once on a daily basis.Typically, drug treatment was initiated 60-80 hours after cell seedingdepending on seeding density. Data collection is controlled by softwareprogram which operates the hardware and allows the user to define thesampling frequency and sampling window. Sampling frequency is defined asthe number of times during an experimental run the beating is sampledand the sampling window is defined as the duration of time that thebeating is actually measured. For example if the sampling frequency is15 minutes and sampling window is for 5 second means that each 15 minutethe system will record beating data for 5 seconds. In a typicalexperiment, prior to compound treatment the sampling frequency is onceevery hour and the sampling window is 20 seconds. 5 min prior totreatment, the cells are sampled every minute for 20 seconds toestablish baseline recording. After treatment, the sampling frequency isevery minute for the first hour, every 5 minutes for the second hour andevery 15 minutes for 3-24 hours. The sampling window for each recordingis fixed at 20 seconds. After the data acquisition, the RTCA Cardiosoftware is used to calculate the parameters such as beating rate,amplitude, beating period, normalized beating rate, normalizedamplitude, and beating rate irregularity (BRI) index and performsubsequent basic statistics, like average and standard deviation andfurther supply EC50 values for dose-response testing.

Terms and Analysis Parameters. Each measured beating cycle correspondsto the excitation-contraction coupling of the cardiomyocytes. Thetypical measured beating pattern is illustrated in FIG. 7 and FIG. 8.The beatings are composed of a sequence of positive peaks (+P) andnegative peaks (−P). The Cell Index difference between one negative peakto the following positive peak is defined as amplitude. The time betweeneach positive peak is defined as beating period and the beating rate iscalculated based on each beating period to derive how many beatingsoccurred in one minute. Three time-related parameters, rise time T_(r),falling time (T_(f), or termed as decay time T_(d)), and half-amplitudewidth T_(IBD50), resolve the temporal beating characteristic.

For data analysis, the related parameters are calculated for everybeating within one recording period and the average and standarddeviation are derived correspondingly. In order to compare the effect oftested compounds, beating rate or amplitude after compound treatment arenormalized to the same time point before compound treatment to obtainthe normalized beating rate or normalized amplitude. In order toevaluate the degree of arrhythmia, the beating rhythm irregularity (BRI)index is derived based on the coefficient of variation (i.e. standarddeviation divided by average) of the beating period during one recordperiod.

Multi-Electrode Array. For the culture of the mouse ES cell-derivedcardiomyocytes a sterilized substrate-integrated planar standard MEA (59TiN electrodes and a grounded reference electrode, 8×8 electrode grid,electrode spacing 200, electrode diameter 30, glass ring (Multi ChannelSystems GmbH, Reutlichen, Germany), 10 μl of the 1:100 dilutedfibronectin solution (F1141, Sigma-Aldrich) was placed exactly on themicroelectrode area of the MEA and incubated for at least 3 hours at 37°C. in an humidified incubator. Afterwards residual coating solution oftaken off and 20 μl with 2×10⁴ cardiomyocytes were placed on the coatedelectrode area and the complete MEA was incubated for another 3 hours at37° C. in the incubator to establish cell adhesion before 1 ml of Cor.Atculture medium was applied. The MEA was connected to the amplifier anddata-acquisition system (Multi Channel Systems) with band pass filtercharacteristics of 0.5 Hz to 1 kHz. Spontaneous electrical activity wasrecorded with software (MC Rack; Multi Channel Systems) (Stett 2003).Data were recorded simultaneously from 59 channels with a samplingfrequency of 10 kHz.

Cardiomyocytes on MEAs were kept in an incubator at 37° C. during thewhole time period of the assay. The cells were equilibrated to the assaybuffer (IMDM+0.1% FCS) for at least 45 min prior to baseline recordingand subsequent substance application. After that, three increasingconcentrations of the test compound were applied consecutively for 15min each. Additional wash-out period with was at least 45 min. Analyzedparameters from extracellular recordings did not alter in a timedependent manner in time-matched control experiments of the vehicle(water or 0.1% DMSO) during all experimental phases.

Raw data from electrode array recordings was analyzed offline. Frequencywas determined as the reciprocal value of the inter spike intervals ofthe field action potentials and field action potential duration wascalculated according to Halbach et al. (2003) (Halbach et al., 2003).Frequency correction of the field potential duration was assessedaccording to Mitchell et al. (Mitchell et al., 1998).

Data are presented as mean values±standard error of the mean in percentof baseline. In order to evaluate compound-induced effects relative tocontrol measurements, differences between the control group and thecompound measurements were tested for statistical significance by meansof unpaired Student's t-test.

Microelectronic monitoring of cardiomyocyte beating. To characterize thebeating, mESCC were seeded in the wells of the E-Plate at a density of40,000 cells/well. The cells were monitored up to 96 hours in culture(FIG. 9A) and the beating activity was recorded at 12, 24, 48, 72 and 96hours (FIG. 9A, arrows) for a total duration of 20 seconds (FIG. 9B).Interestingly, within 24 hours after seeding the cells no consistentbeating activity could be detected even though, under the microscopeclusters of asynchronously beating cardiomyocytes, which have not had anopportunity to form a syncytium could be detected (data not shown).However, within 48 hours the individual clusters begin to form clearconnections and the entire monolayer of cardiac cells in the bottom ofthe well begin to beat in a synchronous manner. Likewise, based onimpedance recording, reproducible beating activity is detected by 48hours (FIG. 9B). The beating rate at 48 hours is approximately 80beats/minute and progressively increases with time reaching almost 250beats/minute after a month in culture. These observations are consistentwith electrophysiological monitoring of action potential duration inmouse ES cell-derived cardiomyocytes (Fijnvandraat et al., 2003).

In order to analyze the curves and quantify beating activity, 3different analysis parameters were derived; T_(IBD50), T_(r) and T_(d).T_(IBD50) is a parameter which measures the duration (ms) between therise and fall of beat cycle at 50% of maximal amplitude. T_(IBD50)values for mESCC at corresponding times are shown in FIG. 9B. At 48hours the T_(IBD50) value is 142±4.6 ms which decreases to 105±2.4 ms by96 hours. The initial rise in amplitude denoted as T_(r) is relativelyfast and depending on the time of recording can vary from 29±5.1 ms to38±1.4 ms (FIG. 9B). The decay time (or the falling time as shown inFIG. 8), denoted as T_(d), which reflects the time the signal decaysfrom 80% of peak height to 20% of peak height is longer compared toT_(r) and can range from 88±7.2 ms to 124±12.0 ms, depending on the timeof recording (FIG. 9B). Interestingly, the kinetics of rise and fall ofimpedance mirrors that of calcium in mouse embryonic cardiomyocytes(Rapila et al., 2008) and it is possible that T_(r) and T_(d) mayreflect the time for two alternating phases of the beating cycle, namelycontraction and relaxation.

To determine if the impedance signal is reflective of physicalcontraction and relaxation cycle of mESCC, we used an inhibitor of themyosin heavy chain ATPase activity, blebbistatin, shown to inhibitcardiomyocyte contraction (Kovacs et al., 2004). As shown in FIG. 9C,blebbistatin treatment of mESCC resulted in significant inhibition ofimpedance signal, which was restored after washing the wells andculturing the cells in media without blebbistatin. Interestingly, atconcentration which blebbistatin inhibited impedance measurement ofbeating activity, no effect on action potential duration was detectedusing field potential recording (FIG. 9D). The inability ofelectrophysiological readout to detect blebbistatin effect has also beenconfirmed using isolated rat and mouse ventricular myocytes, isolatedrabbit ventricle, and Langendorff-perfused rabbit hearts (Dou et al.,2007; Fedorov et al., 2007) indicating that electrophysiologicalreadouts may miss the potential side effect of compounds depending onwhether the compounds affect the electrical or mechanical aspects ofcardiomyocyte contraction. Overall, the results presented thus fardemonstrate that impedance readout can be used to monitor the rhythmiccontraction/relaxation cycle of mESCC in culture over a prolongedduration and in combination with electrophysiological readouts may beable to detect compounds that decouple excitation and contraction.

Pharmacological assessment of mESCC using impedance monitoring. Usingspecific pharmacological modulators of ion channel and non-ion channeltargets, we set out to dissect specific events of theexcitation/contraction cycle in mESCC. First, the time anddose-dependent effect of various ion channel modulators of calcium,sodium and potassium channels were tested (FIGS. 10A-C and FIGS. 11A-C).For these experiments mESCC were thawed, seeded in the wells of theE-Plate, cultured for 3 days, treated with increasing concentrations ofthe compounds and monitored for 24 hours using the RTCA Cardio system.

Assessment of voltage-gated calcium channels. Embryonic stemcell-derived cardiomyocytes are known to undergo spontaneouscontractions due to intracellular calcium oscillations mainly initiatedfrom the sarcoplasmic reticulum (SR) (Sachinidis et al., 2003). It isalso believed that during SR-driven spontaneous activity, theplasmalemmal voltage activated calcium influx could provide acompensatory mechanism for restoring depleted calcium pools in the SR(Rapila et al., 2008). Application of isradipine, a well known voltageactivated L-type calcium channel blocker of the dihydropyridine class(Triggle, 2003) caused a progressive time and dose-dependent decreaseand inhibition of beating activity, indicating that calcium entrythrough L-type calcium channels is required for beating (FIG. 10A). Thehalf maximal dose-response value for isradapine induced inhibition ofbeating activity based on measurement of normalized beating rate andamplitude is 19.7 nM and 42.3 nM respectively (at 5 min time point aftercompound addition; FIG. 12). These values are consistent with efficacyof isradipine tested in isolated rabbit heart (Mellemkjaer et al., 1992)as well as recombinant HEK-293 cells stably expressing the human Cav1.2(Balasubramanian et al., 2009) (FIG. 15). The compound (S)-(−)Bay K 8644is also of the dihydropyridine class, but acts in an agonistic mode toactivate voltage-gated calcium channels (Franckowiak et al., 1985;Schramm et al., 1985). Treatment of mESCC with (S)-(−)Bay K 8644resulted in a dose and time dependent effect that substantiallyincreased the beating rate which persisted for up to 12 hours at higherconcentration and declined by 24 hours (FIG. 10B). The increase inbeating rate is consistent with the reported ionotropic action of thiscompound and the EC50s obtained (77 nM) for beating rate is consistentwith previously published reports using rat ventricular myocytes(Zahradnikova et al., 2007) (33 nM; data not shown).

Assessment of potassium channel modulators. Next, the effect ofChromanol 293B, an inhibitor of slow activating delayed rectifier K⁺current (I_(ks)) (Bosch et al., 1998; Fujisawa et al., 2000; Ono et al.,2000) was tested (FIG. 10C). While at the highest dose (100 μM)Chromanol 293B treatment resulted in complete inhibition ofcardiomyocyte beating activity, at intermediate doses it slows down thebeating rate (69% and 80% of control at 25 μM and 3.13 μM, respectively5 min post compound addition) and also prolongs the beat duration (13.0ms and 21.1 ms at 25 μM and 3 μM respectively and at 5 min post compoundaddition). The I_(ks) is mainly involved in the repolarization phase ofthe action potential and its inhibition by Chromanol 293B leads toincreased action potential duration (APD) of canine ventricle myocytes(Volders et al., 2003) and stem cell-derived human cardiomyocytes (Penget al.) as measured by electrophysiological techniques. The increasedAPD has been shown to slow down the decline of calcium concentrationsand thereby may prolong the contraction phase of cardiomyocytes(Bouchard et al., 1995).

The rapid activating component of the delayed rectifier current (kr) isalso involved in the repolarization phase of cardiac action potentialand is mainly mediated through the ERG channel (Brown, 2005). The effectof E4031, a potent ERG channel inhibitor, was also tested using mESSC ina time and dose-dependent manner (FIG. 11A). As shown, E4031 treatmentinterrupted that normal rhythmicity of beating, especially at highconcentrations (200 nM-800 nM) and resulted in prolonged beat durationswhich are accompanied by plateau oscillations. This phenomenon wastypical of other ERG blockers as well (see next section). At the dosestested the cells appear to recover from the effect of E4031 by 24 hoursafter treatment. Based on normalized beating rate and beat rateirregularity parameter, the half maximal value obtained is 27 nM and 57nM, respectively and is consistent with the reported IC₅₀ for E4031(10nM) using stem cell-derived human cardiomyocytes with patch clamptechnique (Peng et al.).

Assessment of sodium channel modulators. Voltage-gated Na⁺ channels areprimarily responsible for the Na⁺ current and the depolarization phaseof cardiac action potential. Based on gene expression andelectrophysiological data, the Scn5a gene product, which encodes for theα-subunit of voltage-gated Na⁺ channel, is present and functional withinmESCC. Treatment of mESCC with Tetrodotoxin (TTX), a potent andselective inhibitor of voltage-gated Na⁺ channels (Narahashi, 2008), ledto a dose-dependent decrease in beating rate of mESCC which is sustainedat the higher concentrations for the entire duration of 24 hours (FIG.11B). The apparent half-maximal dose-response value obtained forinhibition of mESCC beating is about 0.28 μM (FIG. 12).

Assessment of chronotropic agents. Activation of the sympathetic nervoussystem and neuro-hormonal regulation through the β-adrenergic receptoris a major mechanism controlling rate and contractility of the cardiactissue (Bers, 2002). The protein machinery responding to β-adrenergicreceptor stimulation is present and functional within mESCC and itsagonists are well characterized chronotropic and ionotropic stimulants(Maltsev et al., 1999). Therefore we sought to test whether β-adrenergicreceptor stimulation could be detected by the RTCA Cardio system.Treatment of mESCC with Isoproterenol, a β-adrenergic receptor agonist,increased the contraction frequency of mESCC in a dose andtime-dependent manner while decreasing the overall duration of each beat(FIG. 11C). The overall effect is similar to the L-type calcium channelagonist (S)-(−)Bay K 8644 (FIG. 10B) and is consistent with theobservation that stimulation of β-adrenergic receptors leads toactivation of L-Type calcium channels (Maltsev et al., 1999). The datapresented in this section demonstrates that impedance is a sensitivereadout to assess cardioymocyte beating and its modulation bypharmacologically active compounds which alter cardiacelectrophysiological and/or contractile properties. Compound treatmentproduces both time and concentration-dependent responses which arecaptured in real-time by the RTCA Cardio system. Both acute and longterm assessment of beating activity may provide additional mechanisticinsight as demonstrated for ERG channel inhibitors in the next section.

Example 2: Mechanism-Dependent Compound Toxicity Screening:Identification of Impedance-Based Pro-Arrhythmic Signatures

To test the utility of RTCA Cardio system for pre-clinical cardio-safetyscreening two complementary approaches were undertaken. First, 4 drugswithdrawn from the market due to increased incidence of TdP (Fermin etal., 2003) were screened in a dose-response manner using mESCC (FIG.13A). These compounds have subsequently been shown to also inhibit hERGchannel activity (Brown, 2005). All four compounds significantlyaffected beating rate in a dose-dependent manner (FIG. 13A) and producedbeating irregularities that were consistent with those observed forE4031 in terms of beating waveform, suggesting a common underlyingmechanism (FIG. 13B). We speculate that the plateau oscillationphenomenon observed by hERG channel blockers maybe related to earlyafter depolarization (EAD) effect caused by blocking of the hERG currentleading to premature activation of voltage-dependent L-Type calciumchannels, calcium entry and culminating in premature contractions(Rubart et al., 2005). These signature beating waveforms were alsoobserved for other drugs that are known to interact with and block ERGactivity (FIG. 15 and see below). In order to better quantify thebeating irregularities we derived a kinetic parameter referred to asbeating rhythm irregularity (BRI) index which represents the coefficientof variation (standard deviation divided by average) of beating rateperiods. Based on this parameter we derived half maximal concentrationsfor E4031 (FIG. 12), astemizole, cisapride, droperide and sertindole(FIG. 13A) which are 57 nM, 290 nM, 2700 nM, 2100 nM and 290 nM,respectively. The respective values obtained here are within the rangereported for these compounds using electrophysiological methods (datanot shown). These findings suggest that impedance-based beating profilescould be used in a predictive manner to screen for and identifycompounds that may have off-target interactions with ERG channel.

Next, a compound library containing 50 proarrhythmic and antiarrhythmiccompounds was also screened at 3 doses (10 μM, 1 μM and 0.1 μM) (FIG.15). As shown, all known hERG blockers with the exception of Terfenadinedisplayed beating profiles consistent with those shown in FIG. 13B. Amore extensive dose-response profiling of Terfenadine may be required inorder to observe the signature beating profile similar to other hERGchannel inhibitors. In addition, in this screen, compounds modulatingother ion channel targets such as calcium and sodium also profoundly anddose-dependently affected beating activity.

Example 3: Assessment of Short and Long Term Cardiac Liability UsingImpedance-Based Systems

The true test of any in vitro assay utilized in preclinical safetyassessment depends on its ability to model and predict in vivo effect inthe clinic. Thus far we have shown compounds modulating ion channelactivities in cardiomyocytes can be detected by the RTCA Cardio system.However, there are a number of drugs whose cardiac liability in theclinic extends beyond its propensity to just cause arrhythmia; forexample the chemotherapeutic agent, doxorubicin, has been shown toinduce arrhythmia (Singal et al., 1998) as well as cardiotoxicity byinterfering with mitochondrial function (Minotti et al., 2004).Therefore, we wanted to determine if the RTCA Cardio system incombination with mESCC can model and predict the complex effects ofdoxorubicin. As shown in FIG. 14A, treatment of mESCC with doxorubicinresults in time and dose-dependent decrease in global impedance readout,presumably due to loss of cardiomyocyte viability. Likewise, FIG. 14B,shows the dose- and time-dependent effect of doxorubicin oncardiomyocyte beating within the same assay. Doxorubicin treatment ofmESCC leads to significant decrease in overall beating rate and alsoinduces irregular beating pattern that has features of compounds thatinduce arrhythmia. While it may be difficult to draw direct parallelsbetween in vitro assays and clinical observations, both acute andchronic effect of doxorubicin resulting in arrhythmia has beendocumented in the clinic (Minotti et al., 2004).

The mode of interaction of drugs with various targets withincardiomyocytes may be direct as shown for the various ERG channelblockers and those of sodium and calcium channels or it could also beindirect affecting such processes as the folding or transport of ionchannel proteins to the membrane surface of cardiomyocytes (Dennis etal., 2007) and therefore may go undetected in most conventional safetystudies which are geared towards identification of direct ERG blockers.This point is best exemplified by the compound pentamidine, which in theU.S. is used as a second line of treatment of Pneumocystis cariniipneumonia, a common opportunistic infection in patients with impairedimmune function. Pentamidine has been shown to affect the transport ofthe ERG channel to the membrane in heterologuous expression systems aswell as in cardiac myocytes with repolarization being delayed as adirect consequence (Dennis et al., 2007; Kuryshev et al., 2005). Sincethis compound affects ERG channel activity indirectly, its effect willbe manifested in a time-dependent manner and difficult to capture bystandard patch clamp techniques which are limited to the first hour ofrecording time. We tested the effect of pentamidine on mESCC in a timedependent manner (FIG. 14C). Administration of pentamidine at a finalconcentration of 20 μM has no noticeable effect on beating rate andamplitude well into 900 min after compound addition, at which point thebeating rate slows down and the beating duration is significantlydelayed, most likely due to extended repolarization phase. Theseobservations highlight the importance of monitoring compound effect in atime-dependent manner in order to resolve the effect of compounds onboth early and longer term function of cardiomyocytes and to obtaingreater mechanistic understanding.

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What is claimed is:
 1. A method of determining a beating parameter ofcells that undergo excitation contraction coupling, the methodcomprising: a) providing a cell analysis device comprising a substrateand a sensor that measures cell adhesion or attachment to the substratein millisecond time resolution; b) adding excitable cells capable ofundergoing excitation contraction coupling to the substrate; c)monitoring cell adhesion or attachment of the excitable cells to thesubstrate in millisecond time resolution; and d) calculating one or morebeating parameters from the monitored adhesion.
 2. The method accordingto claim 1, wherein the cell analysis device is an impedance monitoringdevice that measures cell-substrate impedance.
 3. The method accordingto claim 1, wherein the cells are cardiomyocytes.
 4. The methodaccording to claim 1, wherein the cells are stem cell derivedcardiomyocytes.
 5. The method according to claim 1, wherein the cellsare induced pluripotent stem cell (iPS cell) derived cardiomyocytes. 6.The method according to claim 1, wherein the millisecond resolution ischaracterized as consecutive impedance measurements less than 40milliseconds apart.
 7. The method according to claim 6, wherein themillisecond resolution is characterized as consecutive impedancemeasurements less than 20 milliseconds apart.
 8. The method according toclaim 1, wherein the step of calculating one or more parameterscomprises forming a beating curve from the monitored cell adhesion orattachment and deriving the one or more beating parameters from thebeating curve.
 9. The method according to claim 1, wherein the one ormore beating parameters are selected from the group consisting ofbeating rate, beating amplitude, rising time, falling time, beatingperiod, IBD10, IBD50, IBD90, rising slope and falling slope.
 10. Themethod according to claim 1, wherein the one or more beating parametersare selected from the group consisting of normalized beating rate,normalized beating amplitude, beating pattern similarity and beatingrhythm irregularity.
 11. The method according to claim 1, wherein theone or more beating parameters comprises 5 beating parameters.
 12. Themethod according to claim 1, wherein the one or more beating parametersare calculated while the device continues to monitor the cell adhesionor attachment.
 13. The method according to claim 1, further comprisingadding a test compound to the cells, wherein the step of monitoring celladhesion or attachment of the excitable cells is performed after addingthe test compound.
 14. The method according to claim 13, wherein thestep of monitoring cell adhesion or attachment of the excitable cells isperformed before and after adding the test compound.
 15. A method ofdetermining a dose response for a test compound on a cell population,the method comprising: a) determining a beating parameter for differentdoses of a test compound according to the method of claim 1, wherein thetest compound is added at different doses to different populations ofcells; and b) plotting the beating parameters for each dose to form adose response curve.
 16. The method according to claim 15, wherein thebeating parameter for each dose is from a same time point.
 17. Themethod according to claim 15, further comprising determining a IC50 orEC50 value from the dose response curve.
 18. A method for identifying acompound having a potentially cardiotoxic effect, comprising: a)providing a test compound suspected of having a cardiotoxic effect; b)performing the method according to claim 1 to obtain a beating parameterfor the test compound, wherein the cells are cardiomyocytes and whereinthe test compound is added to the cardiomyocytes; and c) comparing thebeating parameter for the test compound to a control beating parameterto identify whether there is a difference between beating parameters andif so, concluding the test compound has the potentially cardiotoxiceffect.
 19. The method according to claim 18, wherein the beatingparameter for the test compound comprises 2 beating parameters, whichare compared to 2 control beating parameters, further wherein the testcompound is concluded to have a cardiotoxic effect if at least one ofthe compared parameters is different.
 20. The method according to claim18, wherein the compound is suspected of being a pro-arrhythmic drugthat may induce arrhythmia.
 21. The method according to claim 18,wherein the step of monitoring the beating of cells is also performedbefore adding the test compound.
 22. The method according to claim 18,wherein the test compound is added at different doses to the cells.